Research and practice of safety education based on deep learning characteristics in science and engineering laboratories
[Objective]Science and engineering laboratories,as primary venues for experimental and practical teaching,are crucial for the safe and stable operation of universities.To ensure safe operations in laboratories,laboratory safety education is a prerequisite,and it represents an important aspect of laboratory safety management.Universities have implemented a series of measures,such as laboratory safety training and assessment,safety lectures for new students,and general laboratory safety education,to improve the effectiveness of laboratory safety education.However,five issues remain in laboratory safety education:excessively emphasizing general education while neglecting specialization and the classification of safety education;prioritizing cognitive education over the development of teaching resources,resulting in a lack of such resources;focusing on theoretical instruction rather than the cultivation of practical abilities,in particular,safety skill training;emphasizing individual education while neglecting safety education for all staff,resulting in a lack of a mechanism ensuring full participation in laboratory safety education;and highlighting system construction without adequate supervision and enforcement,in other words,focusing on results while ignoring process assessment.Through research and exploration,the concept of deep learning can be introduced into laboratory safety education for science and engineering laboratories.This would allow for a comprehensive analysis of the main problems existing in these laboratories and address them through the mechanisms of participation,reflection,guidance,expansion,and evaluation.[Methods]This study aims to fully analyze the essence of deep learning and integrate it into laboratory safety education for science and engineering laboratories.The approach encompasses five mechanisms:participation,reflection,guidance,expansion,and evaluation.These mechanisms facilitate the classification of laboratory safety education courses,enrich teaching resources,strengthen learners'practical abilities,establish a comprehensive system for full participation,and enhance process monitoring.[Results]Introducing the concept of deep learning into safety education for science and engineering laboratories is both practically important and theoretically grounded.First,from the perspective of learners,the concept of deep learning fosters a self-directed learner-centered process and encourages their participation in laboratory safety management and education,thereby elevating their safety awareness and competence.Second,from the perspective of the learning environment,the concept of deep learning seamlessly integrates safety knowledge into education,enhancing its effectiveness.Finally,by leveraging the characteristics of deep learning,learners can continuously upgrade their laboratory safety knowledge and skills through practical reflection and skill expansion,tangibly realizing the achievements of safety education.[Conclusions]Incorporating the concept of deep learning into the safety education system and its evaluation mechanisms would continuously refine the teaching system for laboratory safety education.This would,in turn,enhance the effectiveness of laboratory safety education and facilitate efficient,in-depth development of the system.Furthermore,strengthening the integration and innovation of deep learning technology,as well as teaching resources for laboratory safety education,would contribute to establishing an open,comprehensive,and multilayered safety education system for science and engineering laboratories.
science and engineering laboratoriesdeep learninglaboratory safetysafety educationevaluation system
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